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| classifier.train(); |
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| classifier.addImage(puffinImage1, 'Puffin');classifier.addImage(puffinImage1, 'Puffin'); | |
| classifier.addImage(puffinImage2, 'Puffin');classifier.addImage(puffinImage2, 'Puffin'); | |
| classifier.addImage(puffinImage3, 'Puffin');classifier.addImage(puffinImage3, 'Puffin'); | |
| classifier.addImage(snowLeopardImage1, ‘Snow Leopard’);classifier.addImage(snowLeopardImage1, ‘Snow Leopard’); | |
| classifier.addImage(snowLeopardImage2, ‘Snow Leopard’);classifier.addImage(snowLeopardImage2, ‘Snow Leopard’); |
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| const classifier = features.classification(); |
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| let features = ml5.featureExtractor('MobileNet'); |
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| classifier.predict(gotResult); | |
| function gotResult(results) { | |
| console.log(results); | |
| } |
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| let video = createCapture(VIDEO); | |
| let classifier = ml5.imageClassifier('MobileNet', video); |
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| let classifier = new ml5.ImageClassifier('MobileNet'); |
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| # the following two lines give a two-line status, with the current window highlighted | |
| hardstatus alwayslastline | |
| hardstatus string '%{= kG}[%{G}%H%? %1`%?%{g}][%= %{= kw}%-w%{+b yk} %n*%t%?(%u)%? %{-}%+w %=%{g}][%{B}%m/%d %{W}%C%A%{g}]' | |
| # huge scrollback buffer | |
| defscrollback 5000 | |
| # no welcome message | |
| startup_message off |
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| var scene, | |
| camera, | |
| light, | |
| renderer, | |
| timer, | |
| manager; | |
| function init(){ | |
| manager = new THREE.LoadingManager(); | |
| //Don't start rendering until you finish loading |
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